1. Field of the Invention
Embodiments of the invention described herein pertain to the field of computer systems. More particularly, but not by way of limitation, one or more embodiments of the invention provide a multi-layered data model for determining image choice across a set of audience-specific documents comprising language, regional, regulatory and/or cultural differences.
2. Description of the Related Art
Generating a document for multiple audiences wherein each document is made available in multiple media types using current technology is a time consuming and expensive undertaking. There are no known systems that allow for intelligent selection, positioning and titling of images based on an intended audience. Audiences may have unique language, regional, regulatory and/or cultural characteristics but may be similar and may make use of large portions of the data associated with a similar audience. Media type may comprise markup based documents that are capable of being displayed in a web browser and may also comprise print based media such as for example a paper based catalog.
A document that is targeted to more than one language may also need to take into account the different regional, regulatory, and cultural requirements of the audience for which the document is published. For an audience that is similar to another audience, there is a significant amount of duplicate data entry in addition to the specific modifications required for each intended audience. When underlying data changes, it is not necessarily clear as to what data should be updated in each audience specific document since a specific piece of data may have already been changed to conform to a specific audience. In addition, the generated document needs to be properly formatted regardless of the media type for which the document is generated. Formatting the document for each media type is also time consuming and requires large amounts of maintenance when the data in each version of the document changes further requiring checking the generated documents in each media type to ensure proper formatting. Selection of images based on the intended audience is generally performed by hand.
Current systems for generating documents simply do not provide an easy method for generating multi-audience documents that comprise intelligent selection, positioning and titling of images for multiple output media types. When publishing documents for a global audience, an image that is an appropriate substitute in one instance of the document may not be an adequate substitute in a different instance. French regulations, for instance, prohibit imagery that shows a hypodermic needle whereas in other countries such images are permissible. The same concept is also applicable to language, cultural, and regional or regulatory requirements associated with a particular document. Current systems provide mechanisms for publishing documents in multiple languages, but require brute force entry of multi-lingual data including images in a way that tends require large amounts of duplicate operator entries for similar languages, cultural, regional or regulatory specific embodiments of a document. For example, current systems require a complete set of entries for two languages and the associated images even though they may only differ in a small way such as United Kingdom and United States English versions of a document. In addition, the interfaces of the systems allowing for data entry cannot provide visual clues as to the images used or missing for a given audience since there is no concept of inheritance in current systems. Hence, current systems for generating documents fail to enable the user to determine whether or not a document and its associated images conforms to the expectations or requirements of its intended audience in a visual manner that allows a user to quickly ensure that each regional, regulatory and cultural difference is accounted for in the final generated document.
Furthermore, generating a document for alternate media types requires data that defines the required output format for the particular media type. Current systems that perform this function are generally hardcoded and when a particular piece of data such as in image changes, all target media documents must be manually adjusted and further adjusted for each media output type as well.
For at least the limitations described above there is a need for a system that quickly enables a user to determine whether or not the images associated with a document conforms to the expectations or requirements of its intended audience.